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Collections including paper arxiv:2305.18290

It is a collection of papers that are useful in studying LLM.

Attention Is All You Need

Paper • 1706.03762 • Published Jun 12, 2017 • 61
LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 39
Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Paper • 2305.18290 • Published May 29, 2023 • 58
Lost in the Middle: How Language Models Use Long Contexts

Paper • 2307.03172 • Published Jul 6, 2023 • 40

Fine-Tuning Language Models

Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Paper • 2305.18290 • Published May 29, 2023 • 58

A collection of arXiv papers from Chip Huyen's AI Engineering organized by chapter and ordered by when each appears in the book.

Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning

Paper • 2211.04325 • Published Oct 26, 2022
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Paper • 1810.04805 • Published Oct 11, 2018 • 18
On the Opportunities and Risks of Foundation Models

Paper • 2108.07258 • Published Aug 16, 2021
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks

Paper • 2204.07705 • Published Apr 16, 2022 • 1

Aligning Instruction Tuning with Pre-training

Paper • 2501.09368 • Published Jan 16
Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Paper • 2403.14608 • Published Mar 21, 2024
Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Paper • 2305.18290 • Published May 29, 2023 • 58

Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Paper • 2305.18290 • Published May 29, 2023 • 58

Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Paper • 2305.18290 • Published May 29, 2023 • 58
Towards Efficient and Exact Optimization of Language Model Alignment

Paper • 2402.00856 • Published Feb 1, 2024
A General Theoretical Paradigm to Understand Learning from Human Preferences

Paper • 2310.12036 • Published Oct 18, 2023 • 14
Statistical Rejection Sampling Improves Preference Optimization

Paper • 2309.06657 • Published Sep 13, 2023 • 14

Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Paper • 2305.18290 • Published May 29, 2023 • 58

alignment_24_best

KTO: Model Alignment as Prospect Theoretic Optimization

Paper • 2402.01306 • Published Feb 2, 2024 • 17
Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Paper • 2305.18290 • Published May 29, 2023 • 58
SimPO: Simple Preference Optimization with a Reference-Free Reward

Paper • 2405.14734 • Published May 23, 2024 • 11
Anchored Preference Optimization and Contrastive Revisions: Addressing Underspecification in Alignment

Paper • 2408.06266 • Published Aug 12, 2024 • 10

2023 (and before) Papers of the Year

Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles

Paper • 2306.00989 • Published Jun 1, 2023 • 1
Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Paper • 2305.18290 • Published May 29, 2023 • 58
Scalable Diffusion Models with Transformers

Paper • 2212.09748 • Published Dec 19, 2022 • 18
Matryoshka Representation Learning

Paper • 2205.13147 • Published May 26, 2022 • 11

advancing research

STaR: Bootstrapping Reasoning With Reasoning

Paper • 2203.14465 • Published Mar 28, 2022 • 8
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Paper • 2401.06066 • Published Jan 11, 2024 • 55
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Paper • 2405.04434 • Published May 7, 2024 • 21
Prompt Cache: Modular Attention Reuse for Low-Latency Inference

Paper • 2311.04934 • Published Nov 7, 2023 • 34

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